Financial Math: Quantitative Portfolio Management and Algorithmic Trading
Financial Math is the application of math, statistics, and programming within the finance industry. This course in Quantitative Portfolio Management and Algorithmic Trading is designed for current undergraduate and post-baccalaureate students and provides a rigorous introduction to modern applications in Financial Math through an interdisciplinary curriculum delivered via remote instruction by lecturers and industry experts affiliated with the Financial Math MS program at UChicago.
Financial markets have become increasingly complex, requiring specialized skills to effectively predict opportunities for profit and manage risk. Demand has grown steadily for people who can understand, enhance, and develop complex mathematical models. During the course, you’ll have a chance to learn more about careers in Quant Finance through presentations by our Career Development Office team. We can’t wait to help you explore the exciting world of quantitative finance!
Course Description
This course teaches quantitative finance and algorithmic trading with an approach that emphasizes computation and application. The first half of the course focuses on designing, coding, and testing automated trading strategies in Python, with particular consideration to market models, infrastructure, and order execution. The second half of the course builds on this by covering case studies in quantitative investment that illustrate key issues in allocation, attribution, and risk management. Students will have the chance to learn classic models as well as more modern, computational approaches, all illustrated with application.
Academic Prerequisites
Applicants from any academic major are welcome! We are particularly interested in students with no previous background in finance who are interested in exploring Quantitative Finance as a career option.
Statistics, math, finance and Python programming will be featured. Familiarity in some of these areas is helpful, but there are not strict prerequisites. Some experience in regression and programming is highly recommended, but the course is accessible to motivated students still new to some of these areas.
- Synchronous class meets Mondays, 6:00pm - 9:00pm Central, June 10 - August 9.
- This class will be delivered via remote instruction for Summer 2024.
Mark Hendricks
Mark Hendricks is an Associate Senior Instructional Professor in the Department of Mathematics and as the Deputy Director of Financial Mathematics, he helps manage all aspects of the program. His industry experience includes quantitative research, systematic trading, risk management, for hedge funds and asset managers. Mark also has been a consultant and adviser for firms in trading, private equity, and data analysis.
Mark has taught courses, reviews, and workshops at the graduate level for Financial Math, the Booth School of Business, and the Department of Economics. He has taught portfolio and risk management, asset pricing, valuation, and data analysis, among other things. Mark’s courses emphasize active learning with application and data.
As a Ph.D. candidate for Financial Economics at the University of Chicago’s Booth School and Department of Economics, Mark won awards including a Stevanovich Fellowship and Lee Prize. Mark holds an M.A. in Economics and a B.S. in Mathematics.
Sebastien Donadio
Sebastien Donadio is currently an architect in the Bloomberg CTO office. He has a wide variety of professional experience including being the Chief Technology Officer in a FX/Crypto trading shop, head of software engineering at HC Technologies, quantitative trading strategy software developer at Sun Trading, partner at AienTech, high-frequency trading hedge fund, working as technological leader in creating operating system for the Department of Defense. He also has research experience with Bull, and an IT Credit Risk Manager with Société Générale while in France.
Sebastien has taught various computer science and financial engineering courses for the past fifteen years. This time was spent between the University of Versailles, Columbia University, University of Chicago, NYU. Courses included: Computer Architecture, Parallel Architecture, Operating System, Machine Learning, Advanced Programming, Real-time Smart Systems, Advanced Financial Computing.
Current UChicago Students
Current UChicago students must request term activation prior to self-registration. Self-registration for Summer Quarter occurs through My UChicago and opens on February 14. See the Current UChicago Students page for more information on Summer Quarter registration.
Visiting Undergraduate and Graduate Students
See the Visiting Students page for more information or go here to continue your application.
The cost of this course is $4,635. For details on costs, refunds, or withdrawal deadlines, see the Summer Quarter page.
Admitted visiting students should review the Visiting Undergraduate Summer Students page for information on essential steps to connect to your course, including setting up your CNET ID (email/system login), UChicago Zoom, UChicago VPN, Canvas, library access, and more.